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<a href="_binary_r_b_m_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//used for training the RBM</span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="preprocessor">#include &lt;<a class="code" href="_binary_r_b_m_8h.html">shark/Unsupervised/RBM/BinaryRBM.h</a>&gt;</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="preprocessor">#include &lt;<a class="code" href="_steepest_descent_8h.html">shark/Algorithms/GradientDescent/SteepestDescent.h</a>&gt;</span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span> </div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment">//the problem</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="preprocessor">#include &lt;<a class="code" href="_bars_and_stripes_8h.html">shark/Unsupervised/RBM/Problems/BarsAndStripes.h</a>&gt;</span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span> </div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment">//for evaluation</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="preprocessor">#include &lt;<a class="code" href="analytics_8h.html">shark/Unsupervised/RBM/analytics.h</a>&gt;</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="preprocessor">#include &lt;iostream&gt;</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span> </div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="keyword">using namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a>;</div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="keyword">using namespace </span>std;</div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span> </div>
<div class="foldopen" id="foldopen00015" data-start="{" data-end="}">
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno"><a class="line" href="_binary_r_b_m_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">   15</a></span><span class="keywordtype">int</span> <a class="code hl_function" href="_binary_r_b_m_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a>(){</div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span> </div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span>    <span class="comment">//we first create the problem. in this tutorial, we use BarsAndStripes</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span>    <a class="code hl_class" href="classshark_1_1_bars_and_stripes.html" title="Generates the Bars-And-Stripes problem. In this problem, a 4x4 image has either rows or columns of th...">BarsAndStripes</a> problem;</div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span>    <a class="code hl_class" href="classshark_1_1_unlabeled_data.html" title="Data set for unsupervised learning.">UnlabeledData&lt;RealVector&gt;</a> data = problem.<a class="code hl_function" href="classshark_1_1_bars_and_stripes.html#aa2fc90b392018f6788e48521f48c7dc9" title="Returns all input pattern of the BarsAndStripes problem.">data</a>();</div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span>    </div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span>    <span class="comment">//some constants needed for training</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span>    <span class="keywordtype">size_t</span> numberOfHidden = 32;<span class="comment">//hidden units of the rbm</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span>    <span class="keywordtype">size_t</span> numberOfVisible = problem.<a class="code hl_function" href="classshark_1_1_bars_and_stripes.html#a9d3b38dcb25c55e2bea3dcf1ff260c0e" title="returns the dimensionality of the data">inputDimension</a>();<span class="comment">//visible units of the inputs</span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span> </div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span>    <span class="comment">//create rbm with simple binary units</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span>    <a class="code hl_class" href="classshark_1_1_r_b_m.html" title="stub for the RBM class. at the moment it is just a holder of the parameter set and the Energy.">BinaryRBM</a> rbm(<a class="code hl_variable" href="namespaceshark_1_1random.html#ab5c1547eee483974d008d43f621a2234">random::globalRng</a>);</div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span>    rbm.<a class="code hl_function" href="classshark_1_1_r_b_m.html#a9ef4cbc58af54464387b84111938dd12" title="Creates the structure of the RBM.">setStructure</a>(numberOfVisible,numberOfHidden);</div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span>    </div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span>    <span class="comment">//create derivative to optimize the rbm</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span>    <span class="comment">//we want a simple vanilla CD-1</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span>    <a class="code hl_class" href="classshark_1_1_contrastive_divergence.html" title="Implements k-step Contrastive Divergence described by Hinton et al. (2006).">BinaryCD</a> cd(&amp;rbm);</div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span>    cd.<a class="code hl_function" href="classshark_1_1_contrastive_divergence.html#ad2f9ab74c8ffca4d383827161fa2df90" title="Sets the value of k- the number of steps of the Gibbs Chain.">setK</a>(1);</div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span>    cd.<a class="code hl_function" href="classshark_1_1_contrastive_divergence.html#a2471eeb8e6d309b0fa983fdbc5879d9b" title="Sets the training batch.">setData</a>(data);</div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span> </div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span>    <span class="comment">//generate optimizer</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span>    <a class="code hl_class" href="classshark_1_1_steepest_descent.html" title="Standard steepest descent.">SteepestDescent&lt;&gt;</a> optimizer;</div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span>    optimizer.<a class="code hl_function" href="classshark_1_1_steepest_descent.html#aea92742aa25e250dfa2674edb522212b" title="set momentum parameter">setMomentum</a>(0);</div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span>    optimizer.<a class="code hl_function" href="classshark_1_1_steepest_descent.html#a68b3feecb0210689c16f1b471e60a9da" title="set learning rate">setLearningRate</a>(0.1);</div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span>    </div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span>    <span class="comment">//now we train the rbm and evaluate the mean negative log-likelihood at the end</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span>    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numIterations = 1000;<span class="comment">//iterations for training</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span>    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numTrials = 10;<span class="comment">//number of trials for training</span></div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span>    <span class="keywordtype">double</span> meanResult = 0;</div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span>    <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> trial = 0; trial != numTrials; ++trial) {</div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span>        <a class="code hl_function" href="group__shark__globals.html#gaa2a8823f1241e854ba858d79fd3e37a2" title="Initialize model parameters uniformly at random.">initRandomUniform</a>(rbm, -0.1,0.1);</div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span>        cd.<a class="code hl_function" href="classshark_1_1_abstract_objective_function.html#abe4776a85c4ce622c25f3290fa1395d1">init</a>();</div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span>        optimizer.<a class="code hl_function" href="classshark_1_1_steepest_descent.html#ad8a11c43e286716c78eddcaad85e2c35">init</a>(cd);</div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span> </div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span>        <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> iteration = 0; iteration != numIterations; ++iteration) {</div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span>            optimizer.<a class="code hl_function" href="classshark_1_1_steepest_descent.html#a481c680541979d1827c1b386203ee4e2" title="updates searchdirection and then does simple gradient descent">step</a>(cd);</div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span>        }</div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span>        <span class="comment">//evaluate exact likelihood after training. this is only possible for small problems!</span></div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span>        <span class="keywordtype">double</span> likelihood = <a class="code hl_function" href="namespaceshark.html#a99371d021e025a4f27232feb1246d4e7" title="Estimates the negative log-likelihood of a set of input vectors under the models distribution.">negativeLogLikelihood</a>(rbm,data);</div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span>        std::cout&lt;&lt;trial&lt;&lt;<span class="stringliteral">&quot; &quot;</span>&lt;&lt;likelihood&lt;&lt;std::endl;</div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span>        meanResult +=likelihood;</div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span>    }</div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span>    meanResult /= numTrials;</div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span> </div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span>    <span class="comment">//print the mean performance</span></div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span>    cout &lt;&lt; <span class="stringliteral">&quot;RESULTS: &quot;</span> &lt;&lt; std::endl;</div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span>    cout &lt;&lt; <span class="stringliteral">&quot;======== &quot;</span> &lt;&lt; std::endl;</div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span>    cout &lt;&lt; <span class="stringliteral">&quot;mean negative log likelihood: &quot;</span> &lt;&lt; meanResult &lt;&lt; std::endl;</div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span> </div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span>}</div>
</div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span> </div>
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